ruthgnz / spyscrap

CLI and GUI for OSINT. Are you very exhibited on the Internet? Check it! Twitter, Tinder, Facebook, Google, Yandex, BOE. It uses facial recognition to provide more accurate results.

SpyScrap

This is an OSINT tool. The main purpose is recolect information from different sources like Google, Tinder, Twitter and more. It combines facial recognition methods to filter the results and uses natural language processing for obtaining important entities from the website the user appears. The tool is able to calculate a final score which indicates the amount of public exposition an user has on the Internet. It has two different modules that can work indepently: CLI and Web Interface. Both modules are built using docker and are easy to deploy.

If you like the tool, give us a star! ⭐

CLI

CLI Module for web scraping:

• Tinder
• Instagram
• Yandex
• Google
• Facebook
• BOE
• Twitter

Prerequisites

Docker and docker-compose

Installation

docker build -t spyscrap .
docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap  [options]

You must put the image you want to be used for facial recognition under the shared volume in docker as in the next example:

docker run -ti -v /Users/ruthgnz/Documents/osint/SpyScrap/src/data:/spyscrap/data sp  -t twitter -n "ruth gonzalez novillo" -i ./data/descarga.jpeg

Usage

docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap  [options]

Get Tinder users and store data in sqlite3 database. Tinder Token must be capturen when logging into Tinder App under Local Storage.

docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap -t tinder -k TOKEN		

Search in google. Add -i to download images and do facial recognition Add -p to only search in an specific site Ex: Linkedin

docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap --tag google -n "<name surname>"
docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap --tag google -n "<name surname>" -i <imagePath>
docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap --tag google -n "<name surname>" -i <imagePath>	-p "<Place>"

Search twitter profiles

docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap -t twitter -n "<name surname>" -s <number of twitter pages to search>		

Search facebook profiles Add -i to download images do facial recognition

docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap -t facebook -n "<name surname>"
docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap --tag facebook -n "<name surname>"	-i <imagePath>			

Search instagram profiles Add -i to download instagram profile image and do facial recognition

docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap -t instagram -n "<name surname>"
docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap -t instagram -n "<name surname>" -i <imagePath>			

Search DNI, Names and Surnames in BOE

docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap -t boe -n "<text to search>" -s <number of BOE pages to search>
docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap -t boe -n "<text to search>" -s <number of BOE pages to search>	-e <boolean> -d <init date> -f <final date>			

OTHER EXAMPLES:

  docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap -t tinder -k TOKEN			
  docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap --tag google -n "<name surname>"		
  docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap --tag google -n "<name surname>" -i <imagePath>								
  docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap --tag google -n "<name surname>" -i <imagePath>	-p "<Place>"								
  docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap -t twitter -n "<name surname>" -s <number of twitter pages to search>						
  docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap -t facebook -n "<name surname>"											
  docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap --tag facebook -n "<name surname>"	-i <imagePath>								
  docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap -t instagram -n "<name surname>"												
  docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap -t instagram -n "<name surname>" -i <imagePath> 											
  docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap -t boe -n "<text to search>" -s <number of BOE pages to search>
  docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap -t boe -n "<text to search>" -s <number of BOE pages to search>	-e <boolean> -d <init date> -f <final date>
  docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap main.py -t yandex -k <imgur id> -i <imagePath>
  docker run -ti -v /PATH/TO/SpyScrap/src/data:/spyscrap/data spyscrap main.py -t yandex -i <imgUrl>

All the results are stored in the docker shared volume you must have configured on your localhost when running the container. The first part is the path for your local folder and you can change it. The second part must be the one in the example (/spyscrap/data)

-v /PATH/TO/SpyScrap/src/data:/spyscrap/data

Web Interface

This is a wrapper for the CLI.

Prerequisites

Docker and docker-compose

Installation

cd web
docker-compose up

Once the images are built, open the browser:

http:\\localhost

For searching in Tinder you must put the database.db file created using the CLI in the volume inside the folder:

SpyScrap\web\data

You will also find in this folder the results of all your searches on the web interface.

DISCLAIMER ⚠️

This tool is for educational purposes only.

Please only use this tool on systems you have permission to access! Ethical use only.

Any actions and or activities related to the tools we have created is solely your responsibility. The misuse of the tools we have created can result in criminal charges brought against the persons in question. We will not be held responsible in the event any criminal charges be brought against any individuals misusing the tools we have made to break the law.

Authors ✒️

• Ruth González - @RuthGnz
• Miguel Hernández - @MiguelHzBz

Thanks 🎁

• BBVA Next Technologies SecLab Team

Feel free to collaborate!!

NOTE: Facial recognition is slow. The tool doesn't implement threading, and depends on your computer power. Be patient when the dataset is huge and you are using images to filter the results, specially on the Tinder module.

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⌨️ with ❤️ by @RuthGnz & @MiguelHzBz